MLOps Technical Architect

Veriipro; Atlanta (GA); On-site; USD 150,000 - 190,000; Full time

Job summary

Veriipro is seeking an experienced MLOps Technical Architect to lead the architecture, design, and deployment of enterprise AI/ML, Generative AI, and Agentic AI solutions. You will collaborate with Data Scientists, ML Engineers, DevOps, and Software teams to deliver scalable, production-ready AI systems in a cloud-native environment.

You will design and implement robust ML pipelines, RAG architectures, and AI agents, leveraging Gemini tools and MCP integrations.

Qualifications

• Strong experience in architecting and deploying enterprise AI/ML systems with MLOps.
• Expertise in LLMs, RAG architectures, and AI agent frameworks across cloud platforms.
• Proficiency in cloud-native AI platforms, data preprocessing, feature engineering, and ML pipelines.

Responsibilities

• Collaborate with business and IT stakeholders to identify AI/ML opportunities.
• Architect scalable AI/ML, MLOps, Generative AI, and Agentic AI solutions.
• Lead the design and development of ML models, AI pipelines, and agent workflows.
• Develop, optimize, and automate ML models, pipelines, and orchestration logic.
• Design and deploy LLM-powered apps, RAG pipelines, AI agents, and vector memory systems.
• Build integrations with enterprise systems via APIs, Gemini tools, and MCP-based integrations.
• Partner with Data Scientists, ML Engineers, DevOps, and Software teams for production readiness.
• Drive tech architecture, infra, tooling, and cloud strategy for AI platforms.
• Monitor performance, troubleshoot production issues, and drive improvements.
• Provide updates, guidance, and documentation to stakeholders.
• Identify automation opportunities and operational efficiencies.
• Foster cross-functional collaboration for project delivery.

Skills

Python

Java

Agentic AI frameworks

LangChain/LangGraph

Google ADK

A2A

Semantic Kernel/AutoGen

OpenAI Agent SDK

Gemini Tools

MCP Tools

TensorFlow

PyTorch

AutoML

LLMs

RAG

NLP

GCP

Vertex AI

Kubeflow

Data preprocessing

Feature engineering

GitHub

APIs

Oracle

DB2

PostgreSQL

BigQuery

Cassandra

Big Data

Agile/Scrum

Education

Bachelor's or Master's in Computer Science / AI / Data Science

Tools

GitHub

APIs

Kubeflow

CI/CD for ML

Gemini tools

MCP-based integrations

Job description

We are seeking an experienced MLOps Technical Architect to lead the architecture, design, and deployment of enterprise AI/ML, Generative AI, and Agentic AI solutions. The ideal candidate will have strong expertise in MLOps, cloud-native AI platforms, LLMs, RAG architectures, and AI agent frameworks, with the ability to deliver scalable, production-ready AI solutions.

Technical Skills

• Strong programming experience in Python and Java.
• Hands-on experience with Agentic AI frameworks, including Google ADK, A2A, LangChain/LangGraph, CrewAI, Semantic Kernel/AutoGen, and OpenAI Agent SDK.
• Experience integrating Gemini Tools and Custom MCP (Model Context Protocol) Tools.
• Strong knowledge of TensorFlow, PyTorch, and AutoML for machine learning model development.
• Hands-on experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Natural Language Processing (NLP).
• Experience designing and implementing RAG architectures, including data ingestion, retrieval, hybrid search, and response generation.
• Strong experience with Google Cloud Platform (GCP), Vertex AI, and Kubeflow.
• Experience in data preprocessing, feature engineering, and ML pipeline development.
• Proficiency with GitHub for source control and version management.
• Experience in model development, testing, validation, deployment, and monitoring.
• Strong knowledge of databases including Oracle, DB2, PostgreSQL, BigQuery, Cassandra, and Big Data platforms.
• Experience working in Agile/Scrum environments.

Good to Have

• GPU programming and performance optimization.
• GPU profiling and TensorRT optimization.
• Experience with vector databases and AI model optimization techniques.

Roles and Responsibilities

• Collaborate with business and IT stakeholders to understand business requirements and identify AI/ML opportunities.
• Architect scalable AI/ML, MLOps, Generative AI, and Agentic AI solutions.
• Lead the design and development of machine learning models, AI pipelines, and intelligent agent workflows.
• Develop, optimize, and automate ML models, pipelines, and orchestration logic.
• Design and deploy LLM-powered applications, RAG pipelines, AI agents, and vector-based memory systems.
• Build integrations with enterprise systems using APIs, Gemini tools, and MCP-based integrations.
• Work closely with Data Scientists, ML Engineers, DevOps, and Software Engineering teams to ensure successful deployment and operational excellence.
• Drive technical architecture, infrastructure, tooling, and cloud strategy for AI platforms.
• Monitor solution performance, troubleshoot production issues, and implement continuous improvements.
• Provide timely project updates, technical guidance, and documentation to stakeholders and leadership.
• Identify opportunities for process automation and operational efficiency.
• Foster collaboration across cross-functional teams to ensure successful project delivery.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Experience designing enterprise-scale AI/ML and MLOps platforms.
• Familiarity with cloud-native AI deployment and CI/CD practices for machine learning.